Bioinformatics Tools Research Articles

Hypoxia-induced circRNAs encoded by PPARA are highly expressed in human cardiomyocytes and are potential clinical biomarkers of acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is a serious cardiovascular disease that adversely affects human health. Circular RNAs (circRNAs) are involved in the pathological and physiological processes of AMI, but the biological mechanism of their involvement and their clinical significance remain unknown. We aimed to identify circRNAs that are significantly associated with morbidity in the peripheral blood of patients with AMI and evaluate their diagnostic utility.MethodsHigh-throughput sequencing was used to screen for differentially expressed circRNAs in peripheral blood samples obtained from five patients with AMI and five sex- and age-matched healthy controls. A series of bioinformatics tools and databases were used to determine the biological functional classification and pathway enrichment of the circRNAs based on data obtained from sequencing. A hypoxia model was established and used to evaluate the effect of hypoxia on circRNA expression in human cardiomyocytes. A cytoplasmic separation assay and enzyme resistance assay were employed to identify the biological characteristics of circRNA. Polymerase chain reaction validity testing and receiver operating characteristic (ROC) curve analysis were used to evaluate the utility of circRNA assessments in the diagnosis of AMI.ResultsA large number of circRNAs were found to be differentially expressed in the peripheral blood of patients with AMI, and significantly more of these circRNAs were highly expressed than lowly expressed. The genes encoding these circRNAs have a wide range of effects on various functions in the body. A hypoxic environment promoted the upregulation of circRNA expression in human cardiomyocytes, and hsa_circ_0116795 encoded by PPARA was highly expressed in the peripheral blood of the patients with AMI. In terms of biological characteristics, under physiological conditions, hsa_circ_0116795 (circ_PPARA) was mainly located in the cytoplasm of cardiomyocytes and found to be resistant to exonuclease. The ROC curve analysis showed that the expression levels of circ_PPARA in the peripheral blood of patients with AMI were significantly different from those in the peripheral blood of healthy controls.ConclusionA large number of abnormally expressed circRNAs are detectable in the peripheral blood of patients with AMI. In particular, circ_PPARA is highly expressed in human myocardial cells under hypoxic conditions, and its biological characteristics indicate that it could be employed as a biomarker for the early diagnosis of AMI.

DNA methylation of microRNA-365-1 induces apoptosis of hair follicle stem cells by targeting DAP3

BackgroundDNA methylation is a crucial epigenetic alteration involved in diverse biological processes and diseases. Nevertheless, the precise role of DNA methylation in chemotherapeutic drug-induced alopecia remains unclear. This study examined the role and novel processes of DNA methylation in regulating of chemotherapeutic drug-induced alopecia. MethodsA mouse model of cyclophosphamide (CTX)-induced alopecia was established. Hematoxylin-eosin staining and immunohistochemical staining for the Ki67 proportion and a mitochondrial membrane potential assay (JC-1) were performed to assess the structural integrity and proliferative efficiency of the hair follicle stem cells (HFSCs). Immunofluorescence staining and real-time fluorescence quantitative PCR (RT-qPCR) were performed to determine the expression levels of key HFSC markers, namely Lgr5, CD49f, Sox9, CD200, and FZD10. Differential DNA methylation levels between the normal and CTX-induced model groups were determined through simple methylation sequencing and analyzed using bioinformatics tools. The expression levels of miR-365-1, apoptosis markers, and DAP3 were detected through RT-qPCR and western blotting. In parallel, primary mouse HFSCs were extracted and used as a cell model, which was constructed using 4-hydroperoxycyclophosphamide. The luciferase reporter gene assay was conducted to confirm miR-365-1 binding to DAP3. To measure the expression of relevant indicators, superoxide dismutase (SOD) and malondialdehyde (MDA) kits were used. Methylation-specific PCR (MS-PCR) was performed to determine DNA methylation levels. The regulatory relationship within HFSCs was confirmed through plasmid overexpression of miR-365-1 and DAP3. ResultIn the alopecia areata model, a substantial number of apoptotic cells were observed within the hair follicles on the mouse backs. Immunofluorescence staining revealed that the expression of HFSC markers significantly reduced in the CTX group. Both RT-qPCR and western blotting demonstrated a noteworthy difference in DNA methyltransferase expression. Simple methylation sequencing unveiled that DNA methylation substantially increased within the dorsal skin of the CTX group. Subsequent screening identified miR-365-1 as the most differentially expressed miRNA. miR-365-1 was predicted and confirmed to bind to the target gene DAP3. In the CTX group, SOD and ATP expression markedly reduced, whereas MDA levels were significantly elevated. Cellular investigations revealed 4-HC-induced cell cycle arrest and decreased expression of HFSC markers. MS-PCR indicated hypermethylation modification of miR-365-1 in the 4-HC-induced HFSCs. The luciferase reporter gene experiment confirmed the binding of miR-365-1 to the DAP3 promoter region. miR-365-1 overexpression dramatically reduced apoptotic protein expression in the HFSCs. However, this effect was slightly reversed after DAP3 overexpression in lentivirus. ConclusionThis study explored the occurrence of miR-365-1 DNA methylation in chemotherapeutic drug-induced alopecia. The results unveiled that miR-365-1 reduces cell apoptosis by targeting DAP3 in HFSCs, thereby revealing the role of DNA methylation of the miR-365-1 promoter in chemotherapeutic drug-induced alopecia.

The first molecular characterization of Sarcocystis cameli in the Indian dromedary camels (Camelus dromedarius).

In the present study, tissue samples (tongue, esophagus and heart) were investigated from dromedary camels of India for identification and characterization of Sarcocystis spp. using histopathology, PCR and gene sequencing. Genomic DNA extracted from these tissue samples was used for PCR amplification of the cytochrome c oxidase subunit I gene (cox1) of Sarcocystis spp. and the partial sequence of small subunit ribosomal RNA (18S rRNA) gene of the S. cameli. The PCR products were purified, sequenced and analyzed using bioinformatics tools. Based on phylogenetic analysis of the cox1 gene, the sequences of the present study clustered with those of S. cameli, hosted by dromedary camels of Iraq and a close association was observed with S. masoni hosted by dogs and alpacas of China. Until now, there are no 18S rRNA sequences of S. cameli available in GenBank and this is the first study recording 18S rRNA sequences of S. cameli which were grouped with S. masoni from alpaca of China and guanaco and llama of Argentina in phylogenetic analysis. These findings could be useful for further studies on the characterization through molecular epidemiology, genetic diversity and host specificity of S. cameli.

Navigating the Chemical Space of ENR Inhibitors: A Comprehensive Analysis.

Antimicrobial resistance is a global health threat that requires innovative strategies against drug-resistant bacteria. Our study focuses on enoyl-acyl carrier protein reductases (ENRs), in particular FabI, FabK, FabV, and InhA, as potential antimicrobial agents. Despite their promising potential, the lack of clinical approvals for inhibitors such as triclosan and isoniazid underscores the challenges in achieving preclinical success. In our study, we curated and analyzed a dataset of 1412 small molecules recognized as ENR inhibitors, investigating different structural variants. Using advanced cheminformatic tools, we mapped the physicochemical landscape and identified specific structural features as key determinants of bioactivity. Furthermore, we investigated whether the compounds conform to Lipinski rules, PAINS, and Brenk filters, which are crucial for the advancement of compounds in development pipelines. Furthermore, we investigated structural diversity using four different representations: Chemotype diversity, molecular similarity, t-SNE visualization, molecular complexity, and cluster analysis. By using advanced bioinformatics tools such as matched molecular pairs (MMP) analysis, machine learning, and SHAP analysis, we were able to improve our understanding of the activity cliques and the precise effects of the functional groups. In summary, this chemoinformatic investigation has unraveled the FAB inhibitors and provided insights into rational antimicrobial design, seamlessly integrating computation into the discovery of new antimicrobial agents.

ANÁLISE DE REDE DE INTERAÇÕES MOLECULARES PARA ESTUDAR O DESENCADEAMENTO DE DIABETES E HIPERTENSÃO APÓS A INFECÇÃO POR COVID-19 USANDO FERRAMENTAS DE BIOINFORMÁTICA

Background: The association between COVID-19 infection and the development of new-onset diabetes and hypertension is an emerging area of research. However, a comprehensive understanding of the underlying molecular mechanisms is still lacking. Network analysis using bioinformatics tools can provide valuable insights into the complex molecular interactions involved in these conditions after COVID-19 infection. Objective: This study aims to use bioinformatics tools to analyze the network of molecular interactions related to new-onset diabetes and hypertension following COVID-19 infection. Methods: Data Sources: relevant datasets were collected from NCBI databases, including gene expression profiles and protein-protein interaction information. Data Preprocessing: the collected datasets went through pre-processing to ensure data quality and consistency. Integration of Datasets: the gene expression profiles and protein-protein interaction information were integrated to create a comprehensive dataset that captures the molecular interactions related to new-onset diabetes and hypertension following COVID-19 infection. Network Construction: bioinformatics tool STRING was used to construct a network model represented the molecular interactions identified in the integrated dataset. Network Analysis: the network analysis techniques, included network topology analysis and module identification. Functional Annotation and Pathway Enrichment Analysis: The genes and proteins within the network were functionally annotated using databases KEGG. Results: The network analysis revealed several key proteins and pathways related to the pathogenesis of new-onset diabetes and hypertension after COVID-19 infection. Notably, proteins involved in insulin signaling, glucose metabolism, inflammation, and blood pressure regulation were found to be prominently associated. The signaling pathway and the renin-angiotensin system were identified as key pathways in this context. Conclusion: The study demonstrated the interplay between genetics and protein-protein interactions, particularly within signaling pathways, as pivotal factors in the onset of post-COVID-19 development of new-onset diabetes and hypertension

Dose-Responsive Effects of Iron Supplementation on the Gut Microbiota in Middle-Aged Women.

Oral iron supplementation is the first-line treatment for addressing iron deficiency, a concern particularly relevant to women who are susceptible to sub-optimal iron levels. Nevertheless, the impact of iron supplementation on the gut microbiota of middle-aged women remains unclear. To investigate the association between iron supplementation and the gut microbiota, healthy females aged 40-65 years (n = 56, BMI = 23 ± 2.6 kg/m2) were retrospectively analyzed from the Alberta's Tomorrow Project. Fecal samples along with various lifestyle, diet, and health questionnaires were obtained. The gut microbiota was assessed by 16S rRNA sequencing. Individuals were matched by age and BMI and classified as either taking no iron supplement, a low-dose iron supplement (6-10 mg iron/day), or high-dose iron (>100 mg/day). Compositional and functional analyses of microbiome data in relation to iron supplementation were investigated using various bioinformatics tools. Results revealed that iron supplementation had a dose-dependent effect on microbial communities. Elevated iron intake (>100 mg) was associated with an augmentation of Proteobacteria and a reduction in various taxa, including Akkermansia, Butyricicoccus, Verrucomicrobia, Ruminococcus, Alistipes, and Faecalibacterium. Metagenomic prediction further suggested the upregulation of iron acquisition and siderophore biosynthesis following high iron intake. In conclusion, adequate iron levels are essential for the overall health and wellbeing of women through their various life stages. Our findings offer insights into the complex relationships between iron supplementation and the gut microbiota in middle-aged women and underscore the significance of iron dosage in maintaining optimal gut health.

[Phenotypic and genetic analysis of a Chinese pedigree affected with Hereditary antithrombin deficiency due to a novel variant of SERPINC1 gene].

To analyze the clinical phenotype and genetic characteristics of a Chinese pedigree affected with Hereditary antithrombin deficiency. A pedigree diagnosed at the the Second Affiliated Hospital of Wenzhou Medical University, Yuying Children's Hospital in June, 2020 was selected as the study subject. Plasma prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB), and thrombin time (TT) of the probands and their pedigree members were determined using a STA-R automatic coagulation analyzer. Antithrombin activity (AT: A) and antithrombin antigen (AT: Ag) in plasma were determined with chromogenic substrate and immunonephelometry assays. All exons and flanking sequences of the anticoagulant protein gene SERPINC1 were amplified by PCR and subjected to Sanger sequencing. Candidate variants were verified with bioinformatic tools (PolyPhen-2, SIFT, Mutation Taster and PYMOL) to explore their effect on the function and structural conformation of the protein. The probands (II-2, II-10), their brother (II-5) and sons (III-1, III-8) had shown normal PT, APTT, FIB, and TT, but significantly decreased AT: A and AT: Ag, with their levels being 34%, 57%, 56%, 48%, 53% and 13.51 mg/dL, 13.44 mg/dL, 18.39 mg/dL, 17.36 mg/dL, 17.71 mg/dL, respectively. The remaining pedigree members had normal values. Sanger sequencing revealed that the probands and all affected pedigree members had harbored a heterozygous c.851T>C (p.Met284Thr) missense variant in exon 5 of the SERPINC1 gene. Bioinformatic analysis and simulation suggested that the variant has resulted in alteration of hydrogen bonds at the c.851 position, which may affect the structure of the protein. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as pathogenic (PS1+PM1+PM5+PP1+PP4). The probands and other affected members were all diagnosed with type I hereditary AT deficiency, for which the c.851T>C (p.Met284Thr) variant of the SERPINC1 gene may be accountable.

Long Non-Coding RNAs in Kidney Injury: A Comprehensive Review

Kidney injury, a global health challenge, necessitates a nuanced understanding of molecular intricacies for effective interventions. Long non-coding RNAs (lncRNAs), once dismissed as transcriptional noise, now emerge as pivotal players in orchestrating renal health. Dysregulation of specific lncRNAs like TUG1, MALAT1, H19, and NEAT1 provides molecular signatures, distinguishing physiological states from pathological conditions. In acute kidney injury (AKI), TUG1 and MALAT1 regulate apoptosis, inflammation, and fibrosis. Chronic kidney disease (CKD) involves lncRNAs like H19 and NEAT1 modulating cell proliferation and apoptosis. Beyond diagnostics, lncRNAs actively shape inflammation, apoptosis, and fibrosis, positioning them as master regulators in the intricate ballet of kidney health. Recent strides in research, coupled with cutting-edge genomics and bioinformatics tools, highlight their roles and therapeutic potential. Challenges in understanding their intricate roles and interactions necessitate the exploration of promising avenues, including single-cell RNA sequencing and artificial intelligence, paving the way for personalized interventions and regenerative medicine in kidney diseases.

ReporType: A Flexible Bioinformatics Tool for Targeted Loci Screening and Typing of Infectious Agents.

In response to the pressing need for continuous monitoring of emergence and circulation of pathogens through genomics, it is imperative to keep developing bioinformatics tools that can help in their rapid characterization and classification. Here, we introduce ReporType, a versatile bioinformatics pipeline designed for targeted loci screening and typing of infectious agents. Developed using the snakemake workflow manager, ReporType integrates multiple software for read quality control and de novo assembly, and then applies ABRicate for locus screening, culminating in the production of easily interpretable reports for the identification of pathogen genotypes and/or screening of specific genomic loci. The pipeline accommodates a range of input formats, from Illumina or Oxford Nanopore Technology (ONT) reads (FASTQ) to Sanger sequencing files (AB1), or FASTA files, making it flexible for application in multiple pathogens and with different purposes. ReporType is released with pre-prepared databases for some viruses and bacteria, yet it remains easily configurable to handle custom databases. ReporType performance and functionality were validated through proof-of-concept exercises, encompassing diverse pathogenic species, including viruses such as measles, Newcastle disease virus (NDV), Dengue virus (DENV), influenza, hepatitis C virus (HCV) and Human T-Cell Lymphotropic virus type 1 (HTLV-1), as well as bacteria like Chlamydia trachomatis and Legionella pneumophila. In summary, ReporType emerges as a simple, dynamic and pan-pathogen tool, poised to evolve in tandem with the ever-changing needs of the fields of pathogen genomics, infectious disease epidemiology, and one health bioinformatics. ReporType is freely available at GitHub.

Phosphoproteomic analysis of APP/PS1 mice of Alzheimer's disease by DIA based mass spectrometry analysis with PRM verification

Traditional Chinese medicine has been utilized in China for approximately thousands of years in clinical settings to prevent Alzheimer's disease (AD) and enhance memory, despite the lack of a systematic exploration of its biological underpinnings. Exciting research has corroborated the beneficial effects of tetrahydroxy stilbene glycoside (TSG), an extract derived from Polygonum multiflorum, in delaying learning and memory impairment in a model that mimics AD. Therefore, the primary objective of this study is to investigate the major function of TSG upon protein regulation in AD. Herein, a novel approach, encompassing data independent acquisition (DIA), DIA phosphorylated proteomics, and parallel reaction monitoring (PRM), was utilized to integrate quantitative proteomic data collected from APP/PS1 mouse model exhibiting toxic intracellular aggregation of Aβ. Initially, we deliberated upon both single and multi-dimensional data pertaining to AD model mice. Furthermore, we authenticated disparities in protein phosphorylation quantity and expression, phosphorylation function, and ultimately phosphorylation kinase analysis. In order to validate the results, we utilized PRM ion monitoring technology to identify potential protein or peptide biomarkers. In the mixed samples, targeted detection of 50 target proteins revealed that 26 to 33 target proteins were stably detected by PRM. In summary, our findings provide new candidates for AD biomarker, which have been identified and validated through protein researches conducted on mouse brains. This offers a wealth of potential resources for extensive biomarker validation in neurodegenerative diseases. SignificanceDIA phosphorylated proteomics technique was used to detect and analyze phosphorylated proteins in brain tissues of mice with AD. Data were analyzed by various bioinformatics tools to explore the phosphorylation events and characterize them related to TSG. The results of DIA were further verified by PRM. Besides, we mapped the major metabolite classes emerging from the analyses to key biological pathways implicated in AD to understand the potential roles of the molecules and the interactions in triggering symptom onset and progression of AD. Meanwhile, we clarified that in the context of AD onset and TSG intervention, the changes in proteins, protein phosphorylation, phosphorylation kinases, and the internal connections.

Emerging resistome diversity in clinical Vibrio cholerae strains revealing their role as potential reservoirs of antimicrobial resistance.

This is a unique and novel study delineating the genotyping and subsequent prediction of AMR determinants of Vibrio cholerae revealing the potential of contemporary strains to serve as precursors of severe AMR crisis in cholera. Genotyping of representative strains, VC1 and VC2 was undertaken to characterize antimicrobial resistance genes (ARGs) against chloramphenicol, SXT, nalidixic acid and streptomycin against which they were found to be resistant by antibiogram analysis in our previous investigation. strAB, sxt, sul2, qace∆1-sul1 were detected by PCR. Genome annotation and identification of ARGs with WGS helped to detect the presence of almG, varG, strA (APH(3'')-Ib), strB (APH(6)-Id), sul2, catB9, floR, CRP, dfrA1 genes. Signatures of resistance determinants and protein domains involved in antimicrobial resistance, primarily, efflux of antibiotics were identified on the basis of 30-100% homology to reference proteins. These domains were predicted to be involved in other metabolic functions on the basis of 100% identity with 100% coverage with reference protein and nucleotide sequences and were predicted to be of a diverse taxonomic origin accentuating the influence of the microbiota on AMR acquisition. Sequence analysis of QRDR (quinolone resistance-determining region) revealed SNPs. Cytoscape v3.8.2 was employed to analyse protein-protein interaction of MDR proteins, MdtA and EmrD-2, with nodes of vital AMR pathways. Vital nodes involved in efflux of different classes of antibiotics were found to be absent in VC1 and VC2 justifying the sensitivity of these strains to most antibiotics. The study helped to examine the resistome of VC isolated from recent outbreaks to understand the underlying reason of sensitivity to most antibiotics and also to characterize the ARGs in their genome. It revealed that VC is a reservoir of signatures of resistance determinants and serving as precursors for severe AMR crisis in cholera. This is the first study, to our knowledge, which has scrutinized and presented systematically, information on prospective domains which bear the potential of serving as AMR determinants in VC with the help of bioinformatic tools. This pioneering approach may help in the prediction of AMR landfalls and benefit epidemiological surveillance and early warning systems.

Dig-up Primers: A Pipeline for Identification of Polymorphic Microsatellites Loci within Assemblies of Related Species.

Simple sequence repeats (SSRs) have become one of the most popular molecular markers and are used in numerous fields, including conservation genetics, population genetic studies, and genetic mapping. Advances in next-generation sequencing technology and the growing amount of genomic data are driving the development of bioinformatics tools for SSR marker design. These tools work with different combinations of input data, which can be raw reads or assemblies, and with one or more input datasets. We present here a new strategy and implementation of a simple standalone pipeline that utilizes more than one assembly for the in silico design of PCR primers for microsatellite loci in more than one species. Primers are tested in silico to determine if they are polymorphic, eliminating the need to test time-consuming cross-species amplification in the laboratory. The end result is a set of markers that are in silico polymorphic in all analyzed species and have great potential for the identification of interspecies hybrids. The efficiency of the tool is demonstrated using two examples at different taxonomic levels and with different numbers of input assemblies to generate promising, high-quality SSR markers.

Comprehensive mapping of the AOP-Wiki database: identifying biological and disease gaps.

Introduction: The Adverse Outcome Pathway (AOP) concept facilitates rapid hazard assessment for human health risks. AOPs are constantly evolving, their number is growing, and they are referenced in the AOP-Wiki database, which is supported by the OECD. Here, we present a study that aims at identifying well-defined biological areas, as well as gaps within the AOP-Wiki for future research needs. It does not intend to provide a systematic and comprehensive summary of the available literature on AOPs but summarizes and maps biological knowledge and diseases represented by the already developed AOPs (with OECD endorsed status or under validation). Methods: Knowledge from the AOP-Wiki database were extracted and prepared for analysis using a multi-step procedure. An automatic mapping of the existing information on AOPs (i.e., genes/proteins and diseases) was performed using bioinformatics tools (i.e., overrepresentation analysis using Gene Ontology and DisGeNET), allowing both the classification of AOPs and the development of AOP networks (AOPN). Results: AOPs related to diseases of the genitourinary system, neoplasms and developmental anomalies are the most frequently investigated on the AOP-Wiki. An evaluation of the three priority cases (i.e., immunotoxicity and non-genotoxic carcinogenesis, endocrine and metabolic disruption, and developmental and adult neurotoxicity) of the EU-funded PARC project (Partnership for the Risk Assessment of Chemicals) are presented. These were used to highlight under- and over-represented adverse outcomes and to identify and prioritize gaps for further research. Discussion: These results contribute to a more comprehensive understanding of the adverse effects associated with the molecular events in AOPs, and aid in refining risk assessment for stressors and mitigation strategies. Moreover, the FAIRness (i.e., data which meets principles of findability, accessibility, interoperability, and reusability (FAIR)) of the AOPs appears to be an important consideration for further development.

New Genetic Variants of RUNX2 in Mexican Families Cause Cleidocranial Dysplasia.

Cleidocranial dysplasia (CCD) is an autosomal dominant skeletal dysplasia characterized by persistent open skull sutures with bulging calvaria, hypoplasia, or aplasia of clavicles permitting abnormal opposition of the shoulders; wide public symphysis; short middle phalanx of the fifth fingers; and vertebral, craniofacial, and dental anomalies. It is a rare disease, with a prevalence of 1-9/1,000,000, high penetrance, and variable expression. The gene responsible for CCD is the Runt-related transcription factor 2 (RUNX2) gene. We characterize the clinical, genetic, and bioinformatic results of four CCD cases: two cases within Mexican families with six affected members, nine asymptomatic individuals, and two sporadic cases with CCD, with one hundred healthy controls. Genomic DNA analyses of the RUNX2 gene were performed for Sanger sequencing. Bioinformatics tools were used to predict the function, stability, and structural changes of the mutated RUNX2 proteins. Three novel heterozygous mutations (c.651_652delTA; c.538_539delinsCA; c.662T>A) and a previously reported mutation (c.674G>A) were detected. In silico analysis showed that all mutations had functional, stability-related, and structural alterations in the RUNX2 protein. Our results show novel mutations that enrich the pool of RUNX2 gene mutations with CCD. Moreover, the proband 1 presented clinical data not previously reported that could represent an expanded phenotype of severe expression.

Profiling of differentially expressed MicroRNAs in familial hypercholesterolemia via direct hybridization

BackgroundIndividuals with homozygous familial hypercholesterolemia (HoFH) have a severe clinical problem in their first decade of life, which is not usually present in heterozygous FH (HeFH) individuals. For this latter group of patients, FH diagnosis is mostly severely delayed with a significant increase in the risk of angina, myocardial infarction, peripheral artery disease, stroke, and cardiovascular and all-cause mortality. MethodsThis study used various bioinformatics tools to analyze microarray data and identify critical miRNAs and their target genes associated with FH and its severity. Differentially expressed serum miRNAs from direct hybridization microarray data in three groups of subjects: healthy, HeFH, and HoFH. The differential expressed miRNAs were determined according to a log of fold-change (LFC) <-0.5 or >0.5 and of p < 0.05. Then, we assessed their target genes in silico. Gene ontology (GO) enrichment was applied by Cytoscape. The protein-protein interaction and co-expression network were analyzed by the STRING and GeneMANIA plugins of Cytoscape, respectively. ResultsWe identified increased expression of circulating hsa-miR-604, hsa-miR-652-5p, and hsa-miR-4451 as well as reduced expression of hsa-miR-3140-3p, hsa-miR-550a-5p, and hsa-miR-363-3p in both group of FH vs. healthy subjects. Higher levels of hsa-miR-1183, hsa-miR-1185-1-3p, hsa-miR-122-5p, hsa-miR-19a-3p, hsa-miR-345-3p, and hsa-miR-34c-5p were detected in HeFH in respect to HoFH when compared to healthy subjects. Most upregulated miRNAs mainly affected gene related to cardiac myofibrillogenesis, cholesterol synthesis, RNA editing for apolipoprotein B, and associated with LDL-cholesterol levels. In contrast, down-regulated miRNAs mainly affected gene related to plasma biomarker for coronary artery disease, lipids metabolism, cell adhesion and migration, genetic predictors of type 2 diabetes and cholesterol metabolism. The essential genes were primarily enriched in GO regarding biological regulation, intracellular nucleic acid binding, and the KEGG pathway of TGF-β signaling. ConclusionsThe case-control nature of this study precluded the possibility of assessing the predictive role of the identified differentially expressed miRNAs for cardiovascular events. Therefore, the signature of miRNAs reflecting the pathogenesis of both HeFH and HoFH.

Machine learning predictor PSPire screens for phase-separating proteins lacking intrinsically disordered regions

The burgeoning comprehension of protein phase separation (PS) has ushered in a wealth of bioinformatics tools for the prediction of phase-separating proteins (PSPs). These tools often skew towards PSPs with a high content of intrinsically disordered regions (IDRs), thus frequently undervaluing potential PSPs without IDRs. Nonetheless, PS is not only steered by IDRs but also by the structured modular domains and interactions that aren’t necessarily reflected in amino acid sequences. In this work, we introduce PSPire, a machine learning predictor that incorporates both residue-level and structure-level features for the precise prediction of PSPs. Compared to current PSP predictors, PSPire shows a notable improvement in identifying PSPs without IDRs, which underscores the crucial role of non-IDR, structure-based characteristics in multivalent interactions throughout the PS process. Additionally, our biological validation experiments substantiate the predictive capacity of PSPire, with 9 out of 11 chosen candidate PSPs confirmed to form condensates within cells.

Expression of the RPM1-RIN4-RPS2 complex in two citrus species with contrasting response to Huanglongbing

Objetive/Antecedents. Persian lime (Citrus latifolia) shows a very high level of tolerance to Huanglongbing (HLB). A recent study suggests that genes from the RPM1-RIN4-RPS2 complex could be partly responsible for HLB tolerance in Persian lime, unlike other highly susceptible species such as orange (C. sinensis). The objective of this study was to compare the expression of this gene complex between orange, highly susceptible to HLB, and Persian lime, a tolerant species. Materials and Methods. Sequences of the three genes of the complex for orange and Persian lime were obtained from databases of previously published works, alignments and primer design for gene expression were performed using various bioinformatics tools. Subsequently, tissue samples from symptomatic HLB-infected orange and Persian lime were obtained and infection was confirmed. The expression of the RPM1-RIN4-RPS2 genes was compared using endpoint RT-PCR. Results. The presence of all three genes of the complex was determined in both orange and Persian lime, and it was also determined that they are highly conserved between both species. Additionally, it was observed that there is no differential expression for the RPM1 gene in symptomatic HLB tissue; however, there is a difference in the expression of the RPS2 and RIN4 genes. Conclusion. The results suggest that the contrasting response to HLB could be associated with the activity of the interaction of the RIN4 and RPS2 genes, thus, this could be of interest for citrus genetic improvement aiming at HLB control.

MCSS: microbial community simulator based on structure.

De novo assembly plays a pivotal role in metagenomic analysis, and the incorporation of third-generation sequencing technology can significantly improve the integrity and accuracy of assembly results. Recently, with advancements in sequencing technology (Hi-Fi, ultra-long), several long-read-based bioinformatic tools have been developed. However, the validation of the performance and reliability of these tools is a crucial concern. To address this gap, we present MCSS (microbial community simulator based on structure), which has the capability to generate simulated microbial community and sequencing datasets based on the structure attributes of real microbiome communities. The evaluation results indicate that it can generate simulated communities that exhibit both diversity and similarity to actual community structures. Additionally, MCSS generates synthetic PacBio Hi-Fi and Oxford Nanopore Technologies (ONT) long reads for the species within the simulated community. This innovative tool provides a valuable resource for benchmarking and refining metagenomic analysis methods. Code available at: https://github.com/panlab-bio/mcss.

Integration of genomic and transcriptomic data of inbred mouse models for polygenic obesity and leanness revealed “obese” and “lean” candidate alleles in polyadenylation signals

Most mammalian genes have multiple polyadenylation (PA) sites, and alternative polyadenylation (APA) has been linked to diseases such as obesity. Studies have shown that changes in the polyadenylation signal (PAS) can influence the efficiency of cleavage and affect disease susceptibility and phenotype. In our recent study we used inbred mouse models of polygenic obesity and leanness and identified single-nucleotide polymorphisms in PAS (PAS-SNPs) within several obesity candidate genes, including five with differential expression. Nevertheless, to date, there has been no systematic, whole-genome-level approach aiming to prioritise PAS-SNPs potentially affecting APA. Therefore, in this study, we build upon our previous work by integrating existing genomics data with transcriptomics. DEGs were identified in nine tissues by Affymetrix GeneChip. PA and PAS sites were from the PolyASite 2.0 portal. Prioritisation of candidate PAS-SNPs was performed based on whether they were located in DEG, the type of PAS changes they caused, locations of PA sites relative to PAS, and location(s) and expression(s) of Affymetrix probes within a given gene in various tissues. For the candidates, potential consequences due to the alteration in APA events were investigated using bioinformatics databases and tools. The analysis found 127 PAS-SNPs in 101 DEGs across different tissues and identified 12 high-priority and 7 moderate-priority PAS-SNP candidates in 10 and 7 DEGs, respectively. Candidate PAS-SNPs were in 3′ UTR of 12 protein-coding genes (Lean line: Edil3, Eif2s1, Fbxl3, Hlf, Hsf2bp, Knop1, Lair1, Nmrk1; Fat line: Ehd1, Rpl14, Spon1, Txndc9), introns of four protein-coding genes (Lean line: Abi3bp, Prr16; Fat line: Agmo, Itga7) and intron of one lncRNA (Lean line: 1700086O06Rik). The integration of whole-genome sequencing and transcriptome analyses in this study has identified potential genome-wide candidate SNPs that could affect APA by altering/disrupting PAS motifs and be related to obesity in mice. The data provides a foundation for further research into these PAS-SNPs, their genes, and their contribution to the obesity/leanness phenotype, and contributes a part in explaining missing heritability commonly observed in complex traits.

Pirfenidone alleviates fibrosis by acting on tumour-stroma interplay in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a malignancy with a 5-year survival rate of 12%. The abundant mesenchyme is partly responsible for the malignancy. The antifibrotic therapies have gained attention in recent research. However, the role of pirfenidone, an FDA-approved drug for idiopathic pulmonary fibrosis, remains unclear in PDAC. Data from RNA-seq of patient-derived xenograft (PDX) models treated with pirfenidone were integrated using bioinformatics tools to identify the target of cell types and genes. Using confocal microscopy, qRT-PCR and western blotting, we validated the signalling pathway in tumour cells to regulate the cytokine secretion. Further cocultured system demonstrated the interplay to regulate stroma fibrosis. Finally, mouse models demonstrated the potential of pirfenidone in PDAC. Pirfenidone can remodulate multiple biological pathways, and exerts an antifibrotic effect through inhibiting the secretion of PDGF-bb from tumour cells by downregulating the TGM2/NF-kB/PDGFB pathway. Thus, leading to a subsequent reduction in collagen X and fibronectin secreted by CAFs. Moreover, the mice orthotopic pancreatic tumour models demonstrated the antifibrotic effect and potential to sensitise gemcitabine. Pirfenidone may alter the pancreatic milieu and alleviate fibrosis through the regulation of tumour-stroma interactions via the TGM2/NF-kB/PDGFB signalling pathway, suggesting potential therapeutic benefits in PDAC management.